Crop establishment largely depends on the methods of tillage for seedbed preparation. Seedbed conditions and related problems have recently attracted considerable interest for research. The intensity of the soil compa...Crop establishment largely depends on the methods of tillage for seedbed preparation. Seedbed conditions and related problems have recently attracted considerable interest for research. The intensity of the soil compaction achieved because of tillage is related to the working speed of the implement used. The effect of working speed on indices used for the evaluation of seedbed preparation （index of soil texture, actual tillage depth, soil bulk density and the proposed index of leveling） were investigated by applying four different systems of tillage and using different tillage implements. The relationships of the indices investigated to working speed are also presented graphically for all tillage implements used. All relationships were found to be linear with the working speed and the corresponding coefficients of determination were very close to unity. Useful conclusions, which may be used by extension services for the selection of the proper working speed of the implements used for seedbed preparation, are reached. Finally the general conclusion is that reciprocating harrows may be introduced into energetic tillage systems for seedbed preparation.展开更多
A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information...A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information is available on the optimized water and nitrogen management for yield formation,especially the grain-filling process,under HLSC mode.A three-year field experiment with four nitrogen rates and three irrigation rates of HLSC was conducted to reveal the response of grain-filling parameters,grain weight percentage of spike weight(GPS),spike moisture content(SMC),and winter wheat yield to water and nitrogen rates.The four nitrogen rates were N1(360 kg ha^(-1) pure N),N2(300 kg ha^(-1) pure N),N3(240 kg ha^(-1) pure N),and N4(180 kg ha^(-1) pure N),respectively,and the three irrigation quotas were W1(120 mm),W2(90 mm),and W3(60 mm),respectively.Results showed that the determinate growth function generally performed well in simulating the temporal dynamics of grain weight(0.989<R^(2)<0.999,where R2 is the determination coefficient).The occurrence time of maximum filling rate(T_(max))and active grain-filling period(AGP)increased with the increase in the water or nitrogen rate,whereas the average grain-filling rate(G_(mean))had a decreasing trend.The final 1,000-grain weight(FTGW)increased and then decreased with the increase in the nitrogen rates and increased with the increase in the irrigation rates.The GPS and SMC had a highly significant quadratic polynomial relationship with grain weight and days after anthesis.Nitrogen,irrigation,and year significantly affected the T_(max),AGP,G_(mean),and FTGW.Particularly,the AGP and FTGW were insignificantly different between high seedbed(HLSC-H)and low seedbed(HLSC-L)across the water and nitrogen levels.Moreover,the moderate water and nitrogen supply was more beneficial for grain yield,as well as for spike number and grain number per hectare.The principal component analysis indicated that combining 240-300 kg N ha^(-1) and 90^(-1)20 mm irrigation quota could improve grain-filling efficiency and yield for the HLSC-cultivated winter wheat.展开更多
This study aimed to investigate the task demand of intelligent unmanned fertilizer application in seedling stage of corn planted in full-film double-ditch seedbed,a film identification method based on improved DeepLab...This study aimed to investigate the task demand of intelligent unmanned fertilizer application in seedling stage of corn planted in full-film double-ditch seedbed,a film identification method based on improved DeepLabv3+ identification method for full-film double-ditch corn seedbed was proposed.The differences in performance indicators of the original Deeplabv3+ network taking Xception as the backbone network and the network model that replaced three lightweight backbone networks,MobileNetV2,MobileNetV3 and GhostNet were tested.At the same time,the network models,classical semantic segmentation was introduced to PSPNet and UNet for comparative test.The MIoU of DeepLabv3+ network model that replaced its backbone network increased by 5.01%,and FPS improved by 206%compared with original network,and the model size reduced by 90.3%.The three DeepLabv3+ models after replacing the backbone network were further compressed,and the two-layer expansion convolution with low expansion rate in ASPP was deleted,and the common convolution after feature fusion was replaced by the depthwise separable convolution to obtain a lightweight network model.After testing the improved network model,it was found that the average decline of precision indicators was only 0.17%,FPS raised to 66.5,with an average increase of 25.5%,and the size of the model was compressed to 10.53 MB.Test results showed that,the improved model showed excellent performance,and could provide important technology and method support for the research and development of intelligent topdressing and field management on full-film double-ditch corn seedbed during seedling stage.展开更多
文摘Crop establishment largely depends on the methods of tillage for seedbed preparation. Seedbed conditions and related problems have recently attracted considerable interest for research. The intensity of the soil compaction achieved because of tillage is related to the working speed of the implement used. The effect of working speed on indices used for the evaluation of seedbed preparation （index of soil texture, actual tillage depth, soil bulk density and the proposed index of leveling） were investigated by applying four different systems of tillage and using different tillage implements. The relationships of the indices investigated to working speed are also presented graphically for all tillage implements used. All relationships were found to be linear with the working speed and the corresponding coefficients of determination were very close to unity. Useful conclusions, which may be used by extension services for the selection of the proper working speed of the implements used for seedbed preparation, are reached. Finally the general conclusion is that reciprocating harrows may be introduced into energetic tillage systems for seedbed preparation.
基金supported by the National Key Research and Development Program of China(2023YFD1900802)the China Agriculture Research System of MOF and MARA(CARS-03-19)+2 种基金the National Natural Science Foundation of China(51879267)the Central Public-interest Scientific Institution Basal Research Fund,China(IFI2023-13)the Agricultural Science and Technology Innovation Program(ASTIP),Chinese Academy of Agricultural Sciences。
文摘A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information is available on the optimized water and nitrogen management for yield formation,especially the grain-filling process,under HLSC mode.A three-year field experiment with four nitrogen rates and three irrigation rates of HLSC was conducted to reveal the response of grain-filling parameters,grain weight percentage of spike weight(GPS),spike moisture content(SMC),and winter wheat yield to water and nitrogen rates.The four nitrogen rates were N1(360 kg ha^(-1) pure N),N2(300 kg ha^(-1) pure N),N3(240 kg ha^(-1) pure N),and N4(180 kg ha^(-1) pure N),respectively,and the three irrigation quotas were W1(120 mm),W2(90 mm),and W3(60 mm),respectively.Results showed that the determinate growth function generally performed well in simulating the temporal dynamics of grain weight(0.989<R^(2)<0.999,where R2 is the determination coefficient).The occurrence time of maximum filling rate(T_(max))and active grain-filling period(AGP)increased with the increase in the water or nitrogen rate,whereas the average grain-filling rate(G_(mean))had a decreasing trend.The final 1,000-grain weight(FTGW)increased and then decreased with the increase in the nitrogen rates and increased with the increase in the irrigation rates.The GPS and SMC had a highly significant quadratic polynomial relationship with grain weight and days after anthesis.Nitrogen,irrigation,and year significantly affected the T_(max),AGP,G_(mean),and FTGW.Particularly,the AGP and FTGW were insignificantly different between high seedbed(HLSC-H)and low seedbed(HLSC-L)across the water and nitrogen levels.Moreover,the moderate water and nitrogen supply was more beneficial for grain yield,as well as for spike number and grain number per hectare.The principal component analysis indicated that combining 240-300 kg N ha^(-1) and 90^(-1)20 mm irrigation quota could improve grain-filling efficiency and yield for the HLSC-cultivated winter wheat.
基金supported by the National Natural Science Foundation of China(Grant No.5206500552365029)Outstanding Youth Foundation of Gansu Province(Grant No.20JR10RA560),China Postdoctoral Science Foundation(Grant No.2021M700741).
文摘This study aimed to investigate the task demand of intelligent unmanned fertilizer application in seedling stage of corn planted in full-film double-ditch seedbed,a film identification method based on improved DeepLabv3+ identification method for full-film double-ditch corn seedbed was proposed.The differences in performance indicators of the original Deeplabv3+ network taking Xception as the backbone network and the network model that replaced three lightweight backbone networks,MobileNetV2,MobileNetV3 and GhostNet were tested.At the same time,the network models,classical semantic segmentation was introduced to PSPNet and UNet for comparative test.The MIoU of DeepLabv3+ network model that replaced its backbone network increased by 5.01%,and FPS improved by 206%compared with original network,and the model size reduced by 90.3%.The three DeepLabv3+ models after replacing the backbone network were further compressed,and the two-layer expansion convolution with low expansion rate in ASPP was deleted,and the common convolution after feature fusion was replaced by the depthwise separable convolution to obtain a lightweight network model.After testing the improved network model,it was found that the average decline of precision indicators was only 0.17%,FPS raised to 66.5,with an average increase of 25.5%,and the size of the model was compressed to 10.53 MB.Test results showed that,the improved model showed excellent performance,and could provide important technology and method support for the research and development of intelligent topdressing and field management on full-film double-ditch corn seedbed during seedling stage.
